The present invention relates generally to gas turbine engines, and more specifically, to estimating faults in such engines.
Gas turbine engines are used in aeronautical, marine, and industrial applications. Gradual wear resulting from repetitive cycles over the life of an engine, as well as assembly errors and incidental damage to hardware components, can cause faults in such engines. Hardware component damage may occur, for example, due to foreign object damage and extreme operating conditions. Engine efficiency and life are improved by detecting faults as quickly as possible and then performing needed repairs. Quickly detecting faults and performing needed repairs also facilitates avoiding cascading damage.
In aeronautical applications, gas path or performance related faults are typically detected using flight-to-flight trending of a few key parameters such as exhaust gas temperature. Changes in sensed parameters are identified between a current flight and a previous flight. If multiple parameters are trended, then the pattern in the changes may be sufficiently distinct to allow classification (i.e., diagnosis) as a specific fault. With flight-to-flight trending, data scatter may occur, and such data scatter may be of a same order of magnitude as the fault effects to be identified. Also, while sudden changes in a trended parameter indicate possible faults, such trending does not necessarily assist in identifying, or isolating, the fault.
Methods and systems for estimating engine faults are described. In one embodiment, the method includes the steps of obtaining measured engine quantities at a first operating condition, obtaining measured engine quantities at a second operating condition, and generating an estimated fault vector y based on the measured engine quantities obtained at the first and second operating conditions. Model-based values can also be obtained at the first and second operating conditions and used in connection with generating vector y.
The first and second operating conditions, in an exemplary embodiment, are similar. For example, and with a gas turbine engine used in an aeronautical application, the operating conditions are two cruise points in a single flight. Alternatively, the operating conditions are takeoff points in two separate flights. In another exemplary embodiment, the operating conditions are different. For example, the first operating condition is a takeoff point and the second operating condition is a cruise point.
The estimated fault vector y is generated in accordance with:
y=xR
where, x is a vector of size n where n is a number of sensors and model values, and R is a regressor matrix. The regressor matrix R is generated by simulating engines with no faults with random variations in engine quality, deterioration, sensor bias levels, and operating condition to obtain a first set of sensor readings, and simulating engines with several faults of random magnitude within pre-defined magnitude limits with random variations in engine quality, deterioration, sensor bias levels, and operating condition to obtain a second set of sensor readings.
The fault estimation systems and methods provide the advantage that by using inputs acquired during a single or two consecutive flights or cycles, a fault can be detected during the cycle in which it occurs, or a few cycles later.